Nanotechnology-Enabled Modulation of Reactive Oxygen Species in Cancer and Chronic Inflammation: A Systematic Review of Therapeutic Advances and Translational Challenges

Nanotechnology-Enabled Modulation of Reactive Oxygen Species in Cancer and Chronic Inflammation: A Systematic Review of Therapeutic Advances and Translational Challenges Anticipated or actual start date 01 January 2023 Anticipated completion date 2025 Review question What nanotechnology platforms have been used to spatiotemporally modulate reactive oxygen species (ROS) in cancer and chronic inflammatory conditions, what therapeutic effects do they achieve, and what barriers limit clinical translation? Searches Databases: PubMed (MEDLINE), Scopus (Elsevier), Web of Science Core Collection (Clarivate). Time window: 1 January 2013-31 December 2023. Last search date: 31 December 2023. Language: English. Example strategy (PubMed; adapted per database):(nanoparticle* OR nanozyme* OR "metal-organic framework*" OR MOF OR liposome* OR micelle* OR hydrogel* OR nanocarrier* OR photodynamic OR sonodynamic OR ferroptosis) AND ("reactive oxygen species" OR ROS OR redox OR "oxidative stress") AND (cancer OR tumor OR neoplasm* OR inflammation OR inflammatory OR "tumor microenvironment" OR colitis OR arthritis)Full platform-specific strings and filters provided in Supplementary Methods S1. Types of study to be included Preclinical in vitro and in vivo studies and early/mini clinical studies that evaluate nanotechnology platforms designed to modulate ROS in cancer or chronic inflammatory models. Study designs: experimental lab studies, animal studies, first-in-human/Phase I–II pilot data related to ROS-modulating nanoplatforms. Exclusions: conference abstracts, editorials, non-peer-reviewed opinion, studies on ROS without a nanotechnology component, and nanotechnology studies without ROS relevance or without empirical data. Condition or domain being studied Cancer (solid and hematologic, where applicable) and chronic inflammatory diseases (e.g., rheumatoid arthritis, inflammatory bowel disease, psoriasis, neuroinflammation), focusing on ROS biology and redox-targeted nanomedicine. Participants/population Preclinical: cells and animal models relevant to cancer and chronic inflammatory diseases. Clinical: patients with relevant cancers or chronic inflammatory conditions in early trials of ROS-modulating nanoplatforms. Interventions/exposures Nanotechnology platforms that modulate ROS (generation or scavenging), including but not limited to: metal/oxide nanoparticles (e.g., Fe₃O₄, Au), MOFs/COFs, polymeric/lipid nanocarriers (micelles, liposomes, LPH/LPN), nanozymes (SOD/catalase mimetics), biomimetic (cell-membrane–coated) carriers, PDT/SDT agents, magneto/optothermal systems, ferroptosis-inducing constructs, redox/pH/enzyme/hypoxia-responsive systems, and theranostic composites. Comparator(s)/control Any relevant comparator, including vehicle, standard of care therapy, sham activation, or untreated control. Where absent, single-arm outcomes will be narratively synthesized. Primary outcome(s) Therapeutic efficacy: tumor volume/regression; disease severity indices in inflammation models. Quantitative ROS modulation: intra-/extracellular ROS levels (e.g., H₂O₂, ·OH, O₂⁻), redox biomarkers (e.g., MDA, 4-HNE, 8-oxo-dG), and redox-sensitive pathway activity. Secondary outcome(s) Immune/inflammatory readouts (TNF-α, IL-6, NLRP3 activity; macrophage M1/M2 polarization). Mechanistic endpoints (NRF2/Keap1, PI3K/AKT, MAPK, STAT3; ferroptosis/GPX4). Safety/toxicity (acute and chronic; organ histology; liver/renal enzymes; immunogenicity). Delivery performance (targeting efficiency; organelle targeting; pharmacokinetics/retention). Imaging/theranostic performance (diagnostic sensitivity/specificity; treatment monitoring accuracy). Data extraction (selection and coding) Screening: Two reviewers independently screened titles/abstracts per pre-specified criteria; disagreements resolved by discussion or third reviewer. Full-text review: methodological rigor, relevance to ROS-modulating nanotechnology, and availability of outcome data. Data items: study design; model; nanomaterial class and physicochemical traits; stimulus/trigger; targeting strategy; dosing/activation parameters; outcomes (efficacy, ROS metrics, biomarkers); safety; statistics. Management: records deduplicated in Zotero; extraction into structured spreadsheets. Risk of bias (quality) assessment Preclinical/animal: SYRCLE risk-of-bias tool (randomization, blinding, allocation concealment, outcome assessment, reporting). In vitro: adapted quality checklist (nanosynthesis transparency, assay reproducibility, controls, blinding where feasible). Early clinical: appropriate domain-based assessment (randomization/blinding if applicable), adverse event reporting, and selective reporting bias. Strategy for data synthesis Given heterogeneity in materials, models, and outcomes, a narrative synthesis will be primary. Quantitative summary (descriptive statistics) where outcome homogeneity permits (e.g., percentage tumor reduction; fold-change in cytokines/ROS; targeting efficiency). Meta-analysis was deemed infeasible a priori due to model and outcome diversity; if homogeneous sub-clusters emerge, random-effects models may be considered with sensitivity analyses. Subgroup or subset analyses Disease context: cancer vs chronic inflammation. Nanomaterial class: metal/oxide, polymeric/lipid, MOF/COF, carbon-based, biomimetic. Mechanism: ROS-generating vs ROS-scavenging; ferroptosis-inducing vs antioxidant-restoring. Triggering: endogenous (pH, GSH, hypoxia, enzymes) vs exogenous (light, ultrasound, magnetic/optothermal). Targeting: organelle-targeted (mitochondria/lysosome/nucleus) vs non-organelle. Theranostic vs non-theranostic platforms. Biomarker-stratified vs unstratified studies. Assessment of heterogeneity Conceptual and methodological heterogeneity assessed via study design, models, materials, triggers, and outcome measures; statistical heterogeneity quantified (if meta-analysis is possible) using I² and τ². Dissemination plans Peer-reviewed publication; conference presentations; data and extraction sheets available as supplementary material. (Preprint optional at authors’ discretion.) Contact details Guarantor/Corresponding authorUgwu Okechukwu Paul-Chima, PhD (Biochemistry)Department of Research, Publication and Extension, Kampala International University, Kampala, UgandaEmail: [email protected]; [email protected]: https://orcid.org/0000-0003-3563-3521 Review team Ugwu Okechukwu Paul-Chima¹ (guarantor) Ugwu Melvin Nnaemeka² Ogenyi Fabian C¹ Alum Esther Ugo¹ Val Hyginus Udoka Eze¹ Mariam Basajja³ Ugwu Jovita Nnenna¹ Okon Michael Ben¹ Ugwu Chinyere N¹ Uti Daniel Ejim¹ Egba Simeon Ikechukwu¹ ¹ Department of Research, Publication and Extension, Kampala International University, Kampala, Uganda² Department of Medical Biochemistry, Faculty of Basic Medical Sciences, State University of Medical and Applied Science, Igbo-Eno, Enugu, Nigeria³ Department of Health Care and Data Management, Leiden University, Leiden, The Netherlands Funding None declared. (Update if grant support applies.) Conflicts of interest None declared. (All authors will disclose any potential conflicts.) Stage of review at time of registration Preliminary searches: completed (31 December 2023) Piloting of study selection: completed Formal screening: completed Data extraction: completed Risk of bias: completed Data synthesis: completed / manuscript prepared and submitted Keywords Reactive oxygen species; ROS; redox; spatiotemporal modulation; nanotechnology; nanozymes; MOF; ferroptosis; photodynamic therapy; sonodynamic therapy; cancer; chronic inflammation; theranostics; biomarkers; SYRCLE. Notes Any deviations from the protocol (e.g., addition of new outcomes or subgroups) will be documented with justification in the final report. Given notable inter-assay variability in ROS measurement across studies, standardization issues will be explicitly addressed in the synthesis and limitations.